An evaluation of negative selection algorithm with constraint-based detectors

Autor:	Gerry Dozier, Haiyu Hou
Rok vydání:	2006
Předmět:	Nondeterministic algorithm Constraint (information theory) Mathematical optimization Weighted Majority Algorithm Matching (graph theory) Computer science Population-based incremental learning Output-sensitive algorithm Difference-map algorithm Algorithm FSA-Red Algorithm
Zdroj:	ACM Southeast Regional Conference
DOI:	10.1145/1185448.1185479
Popis:	The Negative Selection Algorithm is an immunology-inspired algorithm for anomaly detection application. This algorithm has been implemented with different pattern representations and various matching rules and successfully applied to a broad range of problems. Recent research shows serious problems with this algorithm in terms of both efficiency and effectiveness. In this paper we evaluated the performance of the algorithm constraint-based representation. We argue that the algorithm and problem representations should be considered separately, and that best performance of the algorithm may be obtained by choosing a proper representation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3986097b8b67e1849c6f3cc5aeb110e3 https://doi.org/10.1145/1185448.1185479 Zobrazit plný text záznamu